Objective: To determine the optimum perimetric criteria for short-wavelength automated perimetry on the basis of probabilistic maps that best discriminate between normal and glaucoma.
Design: Comparative cross-sectional study.
Participants: Ninety-five glaucomatous eyes and 128 normal eyes were included in the study.
Interventions: The subjects underwent retinal nerve fiber layer photographic evaluation and short-wavelength automated perimetry.
Main Outcome Measures: A probabilistic map of differential points for short-wavelength automated perimetry was elaborated, and the number of altered points was calculated for each visual field and level of significance (95%, 98%, 99%, and 99.5%).
Results: The presence of a cluster of four or more points outside 95% normal probability limit showed a good combination of sensitivity and specificity. At deeper levels, P: < 1% and P: < 0.5%, the best combination is achieved with three points outside the normal probability limits.
Conclusions: The optimum criterion to define glaucomatous abnormalities in short-wavelength automated perimetry is the presence of a cluster of four points lower than P: < 5% or a cluster of three points lower than P: < 1%.
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